May a natural lake behave as an efficient Fenton reactor under dark conditions?
; Garcia Einschlag, Fernando Sebastian
; Beamud, Sara Guadalupe
; Temporetti, Pedro Felix
; Pedrozo, Fernando Luis 
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Fecha
09/2019
Editorial
Springer
Revista
International Journal of Energy and Water Resources
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Institución organizadora
ISSN
2538-3604
eISSN
2522-0101
ISBN
Idioma
Inglés
Tipo del evento
Clasificación temática
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Resumen
Phenol degradation experiments were performed to study the potential behavior of the acidic Lake Caviahue (LC) as a dark Fenton reactor under natural conditions and upon H2O2 addition at doses typically used for technological applications. In both cases, to assess the influence of dissolved organic matter present in the lake, control experiments were carried out under identical initial conditions (pH, concentrations of phenol, iron, and H2O2), but in the absence of organic matter. A first set of experiments was performed to test the feasibility of dark Fenton processes under environmental conditions. Lake water samples were used as reaction matrix and catalyst source, whereas phenol and H2O2 were added as model pollutant and oxidant, respectively. H2O2 concentrations used were similar to those reported for rainwater. Results show that phenol can be degraded under all conditions studied and that the amount of phenol consumed depends on both the H2O2 concentration added and the matrix composition LC A second set of experiments was designed to characterize the lake behavior as a natural Fenton reactor upon the addition of H2O2 concentrations typically used for technological applications. Although phenol concentration profiles obtained for LC and the artificial solution show the characteristic behavior of Fenton-like systems, the trends are rather different, since for LC, the lag phase is much longer than that for the artificial matrix. Overall, the results suggest that the Fe(III)-chelating effect of the organic matter present in LC slows down reaction rates, but it does not block phenol degradation through Fenton-like processes.
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